Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Fan, TF | en_US |
dc.contributor.author | Liu, DR | en_US |
dc.contributor.author | Liau, CJ | en_US |
dc.date.accessioned | 2014-12-08T15:25:09Z | - |
dc.date.available | 2014-12-08T15:25:09Z | - |
dc.date.issued | 2005 | en_US |
dc.identifier.isbn | 3-540-26257-1 | en_US |
dc.identifier.issn | 1860-949X | en_US |
dc.identifier.uri | http://hdl.handle.net/11536/17544 | - |
dc.description.abstract | Data mining is an instance of the inductive methodology. Many philosophical considerations for induction can also be carried out for data mining. In particular, the justification of induction has been a long-standing problem in epistemology. This article is a recast of the problem in the context of data mining. We formulate the problem precisely in the rough set-based decision logic and discuss its implications for the research of data mining. | en_US |
dc.language.iso | en_US | en_US |
dc.title | Justification and hypothesis selection in data mining | en_US |
dc.type | Proceedings Paper | en_US |
dc.identifier.journal | Foundations of Data Mining and Knowledge Discovery | en_US |
dc.citation.volume | 6 | en_US |
dc.citation.spage | 119 | en_US |
dc.citation.epage | 130 | en_US |
dc.contributor.department | 資訊管理與財務金融系 註:原資管所+財金所 | zh_TW |
dc.contributor.department | Department of Information Management and Finance | en_US |
dc.identifier.wosnumber | WOS:000232911000007 | - |
Appears in Collections: | Conferences Paper |